Project Summary/Abstract A growing body of research indicates that socioeconomic status (SES) is associated with children?s cognitive development, with children of higher SES demonstrating better cognitive outcomes than their lower SES counterparts. However, research has yet to systematically investigate the extent to which early-life differences in SES are associated with cognitive functioning in later life. Understanding childhood SES as a potential risk/protective factor for later-life cognitive health (CH) is essential not only for better specifying complex etiological pathways to age-associated cognitive health problems, but also for furthering early detection, prevention, and treatment strategies. Guided by cumulative advantage/disadvantage theory, as well as research from the fields of child development, cognitive aging, and life course epidemiology, we aim to (a) investigate whether there are particular components of childhood SES (e.g., parental education vs. income) that are most robustly associated with specific aspects of later life CH (MCI vs. cognitive decline); (b) examine whether better school quality and greater intellectual functioning in adolescence protect individuals with lower childhood SES from long-term CH risks; (c) test adolescent health, educational attainment, and midlife health as mediators within life course pathways of risk and protection from childhood SES to later life CH, and (d) use genetic data to examine whether pathways from childhood SES to CH differ for carriers and non-carriers of the allele APOE ?4. We will achieve these aims by applying advanced statistical methods (e.g., structural equation models, general mixture models) to data from the Wisconsin Longitudinal Study (WLS). The WLS has followed since adolescence approximately 4,500 people who graduated from high school in 1957 and has gathered validated measures of CH from these participants through the age of 72. Respondents? diversity both in terms of childhood SES (e.g., with approximately 20% of the sample having needs-to-income ratios in adolescence at or below poverty level) and in terms of CH in young-old age (e.g., approximately 10% being coded with MCI across multiple sets of criteria) make this dataset ideally suited for the study?s aims. The WLS also uniquely offers high-quality assessments of key measures, including prospective measures of childhood SES (e.g., from tax records), genetic data, state-level administrative data on school quality, and a standardized measure of intellectual functioning in adolescence. Tracking of respondent mortality since young adulthood also allows for modeling selective attrition to yield more reliable estimates of focal associations. Findings from this study are essential to guide future research using data from U.S. national samples that will age into middle and later life over the coming decades. They also will help to inform efforts under NIA?s strategic initiatives (a) to expand existing cohort studies to better identify risk and protective factors for later life cognitive impairment, and (b) to advance research on life course mechanisms and modifiable risk factors concerning socioeconomic disparities and later life health.